Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "45" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 50 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 48 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459865 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.394062 | 5.058606 | -0.973553 | 0.879410 | 1.377579 | 3.673567 | -0.272328 | 13.695917 | 0.7388 | 0.7043 | 0.3519 | nan | nan |
| 2459864 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -1.646006 | 6.108953 | 0.318750 | 1.513440 | 0.248451 | 2.780514 | 1.181537 | 51.907277 | 0.7071 | 0.6632 | 0.3995 | nan | nan |
| 2459863 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.648346 | 2.491445 | 0.260789 | 0.922454 | 0.812384 | 0.259228 | -0.158695 | 24.207978 | 0.7020 | 0.6574 | 0.3905 | nan | nan |
| 2459862 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.427989 | 0.609396 | -0.042249 | 1.411221 | -0.221026 | 2.489502 | 0.100678 | 18.598924 | 0.6880 | 0.6983 | 0.4005 | nan | nan |
| 2459861 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.566652 | -0.125953 | 0.398322 | 1.024401 | 0.635855 | -0.644898 | 0.093811 | 24.430089 | 0.7160 | 0.6820 | 0.3990 | nan | nan |
| 2459860 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.420826 | 0.002227 | 0.373122 | 0.555243 | 0.257826 | 1.932434 | 0.074495 | 21.300498 | 0.7222 | 0.6774 | 0.3995 | nan | nan |
| 2459859 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.538294 | 0.129171 | 0.524761 | 0.864306 | 1.147371 | -1.171329 | -0.102448 | 10.412774 | 0.7256 | 0.6816 | 0.3968 | nan | nan |
| 2459858 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.548724 | -0.029735 | 0.521300 | 0.859047 | 1.894087 | -1.038233 | -0.148954 | 22.414157 | 0.7362 | 0.6879 | 0.4098 | 2.745878 | 2.301430 |
| 2459857 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -0.021937 | -0.219486 | -0.115197 | -0.374516 | 1.547040 | 1.894560 | 0.516719 | 16.422285 | 0.0275 | 0.0251 | 0.0015 | nan | nan |
| 2459856 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.459267 | 0.889520 | 0.477684 | 0.065809 | -0.156639 | 1.201909 | -0.112754 | 20.013957 | 0.7287 | 0.7016 | 0.3939 | 2.993454 | 2.515065 |
| 2459855 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.667857 | 0.882859 | 0.230845 | 0.028688 | 1.094007 | 1.134436 | -0.408647 | 13.553773 | 0.7042 | 0.7098 | 0.4280 | 3.261765 | 2.695675 |
| 2459854 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.742849 | 0.936724 | -0.266831 | -0.408865 | 1.058746 | 1.511798 | 1.720607 | 24.815364 | 0.7295 | 0.7411 | 0.4268 | 2.848527 | 2.456365 |
| 2459853 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.322411 | 0.147994 | -0.388426 | -0.251757 | 1.281082 | 1.614826 | 0.605533 | 27.101867 | 0.7500 | 0.6902 | 0.4187 | 2.990637 | 2.579208 |
| 2459852 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 8.65% | 0.00% | 0.312477 | -0.310792 | -0.864688 | 0.475681 | 0.635865 | 0.973892 | -1.122943 | 1.703720 | 0.8418 | 0.8398 | 0.2314 | 2.743425 | 2.751240 |
| 2459851 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.323272 | -0.899823 | -0.763168 | 0.194252 | -0.262585 | 1.226943 | 0.601334 | 24.768792 | 0.7629 | 0.7528 | 0.3412 | 3.131784 | 2.935389 |
| 2459850 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.822520 | -0.770676 | -0.337865 | -0.158418 | 0.308886 | 1.459648 | 0.111245 | 36.235589 | 0.0488 | 0.0495 | 0.0022 | 1.198563 | 1.198054 |
| 2459849 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.524230 | -0.510927 | 0.245006 | -0.793629 | 1.664474 | 1.060329 | -0.169578 | 24.484781 | 0.0499 | 0.0523 | 0.0020 | 1.204022 | 1.205015 |
| 2459848 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.383336 | -0.498630 | -0.900849 | -1.131271 | 1.541674 | 1.585424 | -0.077816 | 23.432069 | 0.0524 | 0.0521 | 0.0025 | 1.188256 | 1.187993 |
| 2459847 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.135340 | -0.229342 | -0.441984 | -0.617048 | -0.495054 | 1.035548 | -0.463991 | 18.621617 | 0.0410 | 0.0466 | 0.0020 | 1.204234 | 1.206652 |
| 2459846 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | -0.374879 | -0.147548 | -0.771726 | -0.682890 | 1.231890 | 1.375134 | -0.298789 | 11.988057 | 0.0524 | 0.0442 | 0.0026 | 1.215380 | 1.209432 |
| 2459845 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.247311 | -0.151229 | -0.873511 | 0.096950 | 1.509809 | 1.537592 | -0.363344 | 14.004415 | 0.7567 | 0.7665 | 0.3602 | 5.291789 | 4.898833 |
| 2459844 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -0.438611 | 0.846819 | 0.964423 | 1.242493 | 1.832837 | 4.649721 | 1.243927 | 18.352355 | 0.0258 | 0.0247 | 0.0010 | nan | nan |
| 2459843 | digital_ok | 100.00% | 0.66% | 0.66% | 0.00% | 100.00% | 0.00% | -0.925969 | 0.778592 | -0.904342 | -1.155141 | 0.388619 | 0.113210 | -0.507676 | 17.027346 | 0.7568 | 0.7606 | 0.3808 | 4.588113 | 3.786458 |
| 2459840 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | 0.018233 | 2.163239 | -1.693799 | -1.914457 | 1.605644 | 2.442053 | 0.657040 | 0.931361 | 0.0246 | 0.0236 | 0.0013 | nan | nan |
| 2459839 | digital_ok | 0.00% | - | - | - | - | - | -0.674835 | 0.028956 | 0.686177 | 0.775672 | 0.394109 | 0.212453 | 0.409511 | 0.654740 | nan | nan | nan | nan | nan |
| 2459838 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.645928 | 2.018922 | -0.753666 | 0.093917 | 3.051056 | 2.430934 | -0.290755 | 27.026783 | 0.7248 | 0.6602 | 0.4265 | 5.187539 | 4.931978 |
| 2459836 | digital_ok | - | 100.00% | 100.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0314 | 0.0350 | 0.0015 | nan | nan |
| 2459835 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -1.389460 | -0.043912 | -0.638038 | 0.745013 | 14.719252 | 6.003578 | 15.661335 | 27.371574 | 0.0319 | 0.0358 | 0.0034 | nan | nan |
| 2459833 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | -0.994642 | -0.248381 | -0.951538 | -0.767186 | 0.993096 | 4.795321 | 1.187291 | 21.526086 | 0.0269 | 0.0295 | 0.0017 | nan | nan |
| 2459832 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.026876 | 0.413645 | -1.092850 | 0.429003 | 0.883085 | 2.109787 | -0.134458 | 17.670046 | 0.8119 | 0.4982 | 0.6089 | 4.137229 | 3.529207 |
| 2459831 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | -0.964068 | -0.736239 | 1.217695 | 1.477257 | 1.366100 | 3.342578 | 0.458780 | 0.775813 | 0.0255 | 0.0282 | 0.0020 | nan | nan |
| 2459830 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.144941 | 0.594581 | -1.087311 | 0.807571 | -1.441207 | 0.832968 | 0.289353 | 57.350053 | 0.8012 | 0.4871 | 0.6071 | 5.734624 | 4.813778 |
| 2459829 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.305120 | 2.334292 | -0.073563 | 0.242086 | 1.306643 | 3.606556 | 1.026370 | 72.763894 | 0.7380 | 0.6213 | 0.4514 | 0.000000 | 0.000000 |
| 2459828 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.169639 | 0.988667 | -0.149323 | 0.624699 | 1.914056 | 0.315033 | 1.021389 | 22.031588 | 0.7967 | 0.5080 | 0.5802 | 3.378966 | 2.386230 |
| 2459827 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.106978 | 1.284020 | -0.642899 | -0.248805 | -0.122389 | 0.255664 | -0.513082 | 3.022283 | 0.7469 | 0.6298 | 0.4539 | 1.104317 | 0.985382 |
| 2459826 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.162480 | 0.612062 | -0.820218 | 0.051157 | -1.336178 | 0.005720 | 0.272498 | 14.181210 | 0.7907 | 0.5295 | 0.5530 | 7.294896 | 7.503187 |
| 2459825 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.022322 | 0.502805 | -0.925892 | 0.660595 | -0.668290 | 0.038687 | -0.643667 | 0.252718 | 0.7888 | 0.5278 | 0.5614 | 1.350331 | 1.083817 |
| 2459824 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.222986 | 1.945741 | -0.972014 | 0.083162 | -0.299619 | 1.379447 | 0.254403 | 5.843735 | 0.6805 | 0.6658 | 0.4122 | 7.535720 | 9.409277 |
| 2459823 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.332779 | 0.191154 | -0.780729 | 0.652576 | -0.923591 | -0.533018 | 0.586265 | 9.160366 | 0.7398 | 0.5827 | 0.5119 | 3.443867 | 3.416652 |
| 2459822 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.137527 | 0.471937 | -0.523516 | 0.292656 | -0.705607 | -0.632628 | -0.475323 | 0.556394 | 0.7902 | 0.5580 | 0.5558 | 1.515803 | 1.285624 |
| 2459821 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -0.290104 | 0.824591 | -0.712804 | 0.042628 | -0.142679 | -1.026664 | -1.465789 | -0.581420 | 0.7910 | 0.5854 | 0.5540 | 1.546710 | 1.427383 |
| 2459820 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.166427 | 1.061316 | -0.407194 | -0.299264 | 1.704718 | 2.690597 | 0.062792 | 9.821000 | 0.7677 | 0.6659 | 0.4341 | 4.434234 | 4.316832 |
| 2459817 | digital_ok | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 7.89% | -0.407493 | 0.311281 | -0.473605 | 0.151546 | -0.287086 | -1.376161 | -0.588995 | 0.002328 | 0.8136 | 0.6574 | 0.5199 | 1.678646 | 1.619811 |
| 2459816 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 0.419645 | 0.658961 | -1.133848 | 0.875653 | -0.750437 | 0.036013 | 0.410800 | 15.197941 | 0.8470 | 0.5802 | 0.6041 | 3.341161 | 3.191153 |
| 2459815 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | -0.200291 | 0.405767 | -1.112803 | 0.640592 | -0.858784 | -0.729421 | 0.183824 | 11.516964 | 0.8050 | 0.6606 | 0.5327 | 3.453919 | 2.859153 |
| 2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 13.695917 | -0.394062 | 5.058606 | -0.973553 | 0.879410 | 1.377579 | 3.673567 | -0.272328 | 13.695917 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 51.907277 | 6.108953 | -1.646006 | 1.513440 | 0.318750 | 2.780514 | 0.248451 | 51.907277 | 1.181537 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 24.207978 | -0.648346 | 2.491445 | 0.260789 | 0.922454 | 0.812384 | 0.259228 | -0.158695 | 24.207978 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 18.598924 | -0.427989 | 0.609396 | -0.042249 | 1.411221 | -0.221026 | 2.489502 | 0.100678 | 18.598924 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 24.430089 | -0.125953 | -0.566652 | 1.024401 | 0.398322 | -0.644898 | 0.635855 | 24.430089 | 0.093811 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 21.300498 | -0.420826 | 0.002227 | 0.373122 | 0.555243 | 0.257826 | 1.932434 | 0.074495 | 21.300498 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 10.412774 | -0.538294 | 0.129171 | 0.524761 | 0.864306 | 1.147371 | -1.171329 | -0.102448 | 10.412774 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 22.414157 | -0.029735 | -0.548724 | 0.859047 | 0.521300 | -1.038233 | 1.894087 | 22.414157 | -0.148954 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 16.422285 | -0.219486 | -0.021937 | -0.374516 | -0.115197 | 1.894560 | 1.547040 | 16.422285 | 0.516719 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 20.013957 | -0.459267 | 0.889520 | 0.477684 | 0.065809 | -0.156639 | 1.201909 | -0.112754 | 20.013957 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 13.553773 | 0.882859 | -0.667857 | 0.028688 | 0.230845 | 1.134436 | 1.094007 | 13.553773 | -0.408647 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 24.815364 | 0.936724 | -0.742849 | -0.408865 | -0.266831 | 1.511798 | 1.058746 | 24.815364 | 1.720607 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 27.101867 | 0.147994 | -0.322411 | -0.251757 | -0.388426 | 1.614826 | 1.281082 | 27.101867 | 0.605533 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 1.703720 | 0.312477 | -0.310792 | -0.864688 | 0.475681 | 0.635865 | 0.973892 | -1.122943 | 1.703720 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 24.768792 | -0.323272 | -0.899823 | -0.763168 | 0.194252 | -0.262585 | 1.226943 | 0.601334 | 24.768792 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 36.235589 | -0.822520 | -0.770676 | -0.337865 | -0.158418 | 0.308886 | 1.459648 | 0.111245 | 36.235589 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 24.484781 | -0.524230 | -0.510927 | 0.245006 | -0.793629 | 1.664474 | 1.060329 | -0.169578 | 24.484781 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 23.432069 | -0.498630 | -0.383336 | -1.131271 | -0.900849 | 1.585424 | 1.541674 | 23.432069 | -0.077816 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 18.621617 | -0.229342 | -0.135340 | -0.617048 | -0.441984 | 1.035548 | -0.495054 | 18.621617 | -0.463991 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 11.988057 | -0.374879 | -0.147548 | -0.771726 | -0.682890 | 1.231890 | 1.375134 | -0.298789 | 11.988057 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 14.004415 | -0.151229 | 0.247311 | 0.096950 | -0.873511 | 1.537592 | 1.509809 | 14.004415 | -0.363344 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 18.352355 | -0.438611 | 0.846819 | 0.964423 | 1.242493 | 1.832837 | 4.649721 | 1.243927 | 18.352355 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 17.027346 | 0.778592 | -0.925969 | -1.155141 | -0.904342 | 0.113210 | 0.388619 | 17.027346 | -0.507676 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Variability | 2.442053 | 0.018233 | 2.163239 | -1.693799 | -1.914457 | 1.605644 | 2.442053 | 0.657040 | 0.931361 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Power | 0.775672 | 0.028956 | -0.674835 | 0.775672 | 0.686177 | 0.212453 | 0.394109 | 0.654740 | 0.409511 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 27.026783 | 2.018922 | -0.645928 | 0.093917 | -0.753666 | 2.430934 | 3.051056 | 27.026783 | -0.290755 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 27.371574 | -0.043912 | -1.389460 | 0.745013 | -0.638038 | 6.003578 | 14.719252 | 27.371574 | 15.661335 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 21.526086 | -0.248381 | -0.994642 | -0.767186 | -0.951538 | 4.795321 | 0.993096 | 21.526086 | 1.187291 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 17.670046 | 0.026876 | 0.413645 | -1.092850 | 0.429003 | 0.883085 | 2.109787 | -0.134458 | 17.670046 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Variability | 3.342578 | -0.964068 | -0.736239 | 1.217695 | 1.477257 | 1.366100 | 3.342578 | 0.458780 | 0.775813 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 57.350053 | -0.144941 | 0.594581 | -1.087311 | 0.807571 | -1.441207 | 0.832968 | 0.289353 | 57.350053 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 72.763894 | 2.334292 | -0.305120 | 0.242086 | -0.073563 | 3.606556 | 1.306643 | 72.763894 | 1.026370 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 22.031588 | 0.988667 | 0.169639 | 0.624699 | -0.149323 | 0.315033 | 1.914056 | 22.031588 | 1.021389 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 3.022283 | 0.106978 | 1.284020 | -0.642899 | -0.248805 | -0.122389 | 0.255664 | -0.513082 | 3.022283 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 14.181210 | 0.612062 | 0.162480 | 0.051157 | -0.820218 | 0.005720 | -1.336178 | 14.181210 | 0.272498 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Power | 0.660595 | 0.502805 | -0.022322 | 0.660595 | -0.925892 | 0.038687 | -0.668290 | 0.252718 | -0.643667 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 5.843735 | -0.222986 | 1.945741 | -0.972014 | 0.083162 | -0.299619 | 1.379447 | 0.254403 | 5.843735 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 9.160366 | 0.191154 | 0.332779 | 0.652576 | -0.780729 | -0.533018 | -0.923591 | 9.160366 | 0.586265 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 0.556394 | 0.137527 | 0.471937 | -0.523516 | 0.292656 | -0.705607 | -0.632628 | -0.475323 | 0.556394 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Shape | 0.824591 | 0.824591 | -0.290104 | 0.042628 | -0.712804 | -1.026664 | -0.142679 | -0.581420 | -1.465789 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 9.821000 | -0.166427 | 1.061316 | -0.407194 | -0.299264 | 1.704718 | 2.690597 | 0.062792 | 9.821000 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Shape | 0.311281 | -0.407493 | 0.311281 | -0.473605 | 0.151546 | -0.287086 | -1.376161 | -0.588995 | 0.002328 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 15.197941 | 0.658961 | 0.419645 | 0.875653 | -1.133848 | 0.036013 | -0.750437 | 15.197941 | 0.410800 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Temporal Discontinuties | 11.516964 | 0.405767 | -0.200291 | 0.640592 | -1.112803 | -0.729421 | -0.858784 | 11.516964 | 0.183824 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 45 | N05 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |